The UMTS Network and Radio Access Technology: Air Interface Techniques for Future Mobile Systems
Jonathan P. Castro
Copyright © 2001 John Wiley & Sons Ltd
Print ISBN 0-471-81375-3 Online ISBN 0-470-84172-9D
EPLOYING
3G N
ETWORKS
7.1 B
ACKGROUND
Logically deploying 3G networks implies dimensioning and implementing corresponding
elements within a geographical area, where an operator would desire to offer advanced
mobile communications services, e.g. voice, mobile Internet, video-telephony, etc.
In the preceding chapters we have outlined the service requirements and technical speci-
fications of the UMTS solution. In this chapter we aim to describe the application of the
proposed solutions and go through the process of designing a network to provide UMTS
services.
Before describing the results of a field study with reference-parameters based on real
scenarios, we provide the necessary principles for dimensioning and implementing a 3G
network using UMTS technology. We then present results of dimensioning and intro-
duce the functional capabilities of the selected elements.
7.2 N
ETWORK
D
IMENSIONING
P
RINCIPLES
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and classical optimization, the main output consists of the identification of sites for BS
(or node B) location. The latter will depend on the projected service strategy and the BS
range and capacity. The service strategy will take into account the traffic flow generated
based on the subscriber profiles of service utilization levels and population densities.
The radio coverage task will include or use the multi-path channel models, and refer-
ence service rates illustrated in Chapter 2.
System dimensioning involves the optimization of coverage and capacity based on mac-
rocells and microcells in densely populated areas. It aims to take into account the asym-
metry of traffic in the UL and DL and includes in the optimization the TDD mode to
maximize capacity and flexibility in micro- and picocells.
Network configuration and verification consolidates the coverage and site location ex-
ercise by starting a process for the integrated solution of radio and core elements. Based
on the capacity and service target requirements, the 3G system architecture is set for the
node Bs and CS and PS elements in the core network side. It also looks at the impact on
the transmission subsystem.
Implementation and deployment completes the 3G-network design process by realizing
the projected site locations, service target requirements and time to service. It takes into
account the solution adopted for the network deployment, e.g. sharing sites with exist-
ing 2G BSs and evolution of CN elements, or a complete new overlay network on the
top of the existing 2G system. It may also apply to a totally green field network, i.e. a
new deployment. It will also take into account the hierarchy of the network, i.e. the
macro- and microlayers where applicable.
When deploying in the macrocell environment primarily with the FDD mode or
WCDMA technology, the implementation will take into account the coverage depend-
ency on the transmission rates and technology availability in terms of antenna configu-
ration and interference minimizing features. Thus, the four actions or steps outlined
above do have an iterative process.
7.2.1 Coverage and Capacity Trade-off in the FDD Mode
From the practical side as mentioned in earlier chapters and Section 7.4 of this chapter,
in the FDD mode, which uses WCDMA techniques, the interference increases with the
7.2.1.1 Soft Handover and Orthogonality
We described soft handover in Chapter 4 from the design side; here we look at it from
the performance and dimensioning side. In this context, a MS performs handover when
the signal strength of a neighbouring cell exceeds the signal strength of the current cell
with a given threshold. In soft handover position, a MS connects to more than one BS
simultaneously. Thus, the FDD mode uses soft handover
3
to minimize interference into
neighbouring cells and thereby improve performance through macro diversity, i.e. we
combine all the paths together to get a better signal quality. We also reduce power
originating from two or more BSs to reach the same mobile’s E
b
/N
0
requirement while
we combine the paths.
We separate the information signal of different users by assigning to each one a differ-
ent broadband and time limited, user specific carrier signal derived from orthogonal
code sequences (e.g. OVSF codes). When completely orthogonal
4
, we can perfectly
separate synchronously transmitted and received signals. However, this does not occur
in the UL for example, due to different propagation paths, i.e. different distances with
different time delays. In the DL even if all signals originate from a single point and the
parallel code channels can be synchronized there is still not perfect signal separation. As
a result, we cannot maintain complete orthogonality due to multipath propagation, and
we have to use orthogonality compensation factors as noted in Chapter 2.
7.3 P
ARAMETERS FOR
M
TrrpuÃhqÃGÃ9hhÃShrHrqvÃ9hhÃShr
CvtuÃ9hhÃShr
Figure 7.2 Transmission rates and coverage.
7.3.1 Circuit and Packet Switched Services
When dimensioning a 3G network in the FDD mode, e.g. the number of concurrent
channels derived to cope with the different service requirements becomes the main in-
put of the link budget analysis. Thus, if we have to manage traffic beyond a cell loading
of 30%, any small load variation will have direct impact on the cell radius. We then
have to achieve a dimensioning to meet the peak traffic during the busy hour in order to
obtain a stable network. This stability will depend on how we treat the different types of
service, i.e. Real Time (RT) or Circuit Switched and Non Real Time (NRT) or packet
switched types.
7.3.1.1 Circuit Switched (CS)
To dimension capacity for CS services we can follow the classical approach, i.e. given
the offered load (Erlangs) and the blocking rate, we derive from the traffic assumptions
the offered traffic at the busy hour per cell (Erlang). Here we would assume the cell
radius gets optimized iteratively with the link budget. Then, from Erlang B table we
would determine the number of concurrent channels required during the busy hour for a
given blocking rate.
Although the traditional solution may allow us to estimate CS capacity easily, it may
also over dimension the required number of channels. Thus, it seems imperative that we
use the multi-service Erlang B formulation and pool the resources for better availability
on demand. This implies that we offer the CS channels depending on the required num-
ber, e.g. if one service requires 2 channels and the other 10, both can benefit from the
pool, which may contain 20 channels. The latter would also imply that we could use
different blocking rates for each service. For example, voice calls can tolerate degrada-
tion better than video calls.
7.3.1.2 Packet Switched Services
As in the CS, although with more sophistication, we also need to estimate the number of
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"
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xÃ6vhyÃvÃUÃrp
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($
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89A
Figure 7.3 Peak arrival rate.
Utilizing the upper 95% time probability of the packet arrival rate (Figure 7.3) and ap-
plying the typical packet length we translated back into kbps. We then calculate the
number of channels (ch) dividing by the service bearer rate r, i.e. ch = h (kbps)/r. We
can summarize the process as: Chs = (1/Serv Rate) × (1/Serv Delay) × CDFp{(m/Serv
delay ×
z
),95%), where CDFp(x,y) corresponds to the point of probability on the CDF
associated with Poisson’s law of mean x, and where m represents the mean offered data
rate in kbps. We should note here that this process can be inefficient with low traffic in
Subscribers
Year: 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
2G 750 1000 900 600 400 300 200 150 100 50
3G 0 0 300 700 1000 1200 1400 1500 1600 1700
Total 750 1000 1200 1300 1400 1500 1600 1650 1700 1750
In Table 7.2 we illustrate the subscriber growth beginning in 2002 when penetration of
data has already reached about 30% of the total traffic. Here we assume that GPRS car-
rying wireless IP type services has grown to non-negligible levels right before the intro-
duction of UMTS. Despite the stretch to a 15-year period, 2005 stands again as the
breaking point towards full predominance of multimedia services. Nonetheless, as in the
projections of the 10-year period, voice only services will remain a good 25% of all
traffic.
Table 7.2 Subscriber Growth Within a 15-year Period (in 1000s)
Ã
Subscribers
Year: 2002 2003 2004 2005 2007 2009 2011 2013 2015 2017
Voice 900 600 400 300 150 100 50 0 0 0
Voice
+ data
300 700 1000 1200 1450 1550 1650 1750 1800 1850
Total 1200 1300 1400 1500 1600 1650 1700 1750 1800 1850
After 2005 in both cases the subscriber growth appears low. This can reflect the fact
that the overall penetration of mobile services in the region begins to reach its limits or
that the market share between operators starts to stabilize. Thus, for all practical pur-
poses, in particular for the network dimensioning exercise in this field study, we con-
sider primarily the data from 2002 to 2005 from Table 7.2.
_______
7
The forecast has harmonized numbers, which do not apply to any operator or service provider in particular.
Deploying 3G Networks 253
7.6 C
ELLULAR
C
OVERAGE
P
LANNING
I
SSUES
Before discussing the fundamental parameters, assumptions and planning methodology,
we select a region with a typical subscriber population and complex geographical area
for cellular planning, e.g. mountainous landscape with large canyons and valleys, as
well as hilly cities.
7.6.1 The Coverage Concept
As illustrated in Figure 7.4 the ideal UMTS coverage concerns all types of environ-
ments, i.e. in buildings (picocells), urban (microcells), suburban (macrocells), and
global (global cells). However, at this time we cover mainly picocells to macrocells.
While FDD coverage here may apply primarily
9
to macrocells, the TDD solution ap-
plies more to pico- and microcells. Figure 7.5 shows an option for combining the UTRA
technologies for maximum coverage.
_______
8
The operator’s initiative and creativity on new services offering product packages and a business approach
will make a large difference. It will not depend only on Internet traffic.
9
The FDD also applies to microcells, and it is not only for use in picocells.
Deploying 3G Networks 255
for the number of sites or cells required for each service environment. It will also allow
estimation of RF unit number according to the number of sectors per site.
_______
11
Regulators in some countries are demanding only 50% initial coverage.
256 The UMTS Network and Radio Access Technology
Ã
È
È
!È
"È
#È
$È
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&È
'È
(È
Total size (km
2
) 4067.00 6741.00
Morphology distribution (km
2
)
Dense urban 2.33 2.37
Urban 9.90 10.60
Commercial/industrial 101.00 138.00
Suburban 387.00 617.00
Forest 1270.00 1961.00
Open 2297.00 4012.00
Morphology distribution
Dense urban (%) 0.06 0.04
Urban (%) 0.24 0.16
Commercial/industrial (%) 2.48 2.05
Suburban (%) 9.52 9.15
Forest (%) 31.23 29.09
Open (%) 56.48 59.52
Table 7.4 illustrates the service quality assumptions for projected radio bearer services
in UMTS. The transmission rates or bearers corresponding to the service environments
represent the most common services. On the other hand, we do not necessarily exclude
speech, LCD 384, LCD 2048, and UDD 2048. For example, voice service may have the
following assumptions: Adaptive Multi Rate (AMR) codec with a bit-rate of 12.2 kbits/
s and with 50% voice activity factor. We can also assume 20 mE/subs with the follow-
ing average holding times per subscriber:
holding time of a mobile originated call 75 s
LCP 95%
Indoor
LCP 95%
Indoor
LCP 95%
Indoor
LCP 95%
Indoor
LCP 90%
Suburban Indoor
LCP 90%
Indoor
LCP 90%
Indoor
LCP 90%
Indoor
LCP 90%
Forest In-car LCP
90%
In-car LCP
90%
In-car LCP
90%
In-car LCP
90%
Open In-car LCP
90%
In-car LCP
Bearer LCD144 (mErl) 0.25 0.25 0.25 0.25 0.25 0.25
The traffic data, i.e. Unrestricted Delay Data (UDD) and Low delay Circuit Switch Data
(LCD) for the different environments (Dense Urban (DU), Urban (U), Industrial (IND),
Suburban (SU), Forest (FO), and Open (OP)), represent the possible traffic flow in the
3G network. We provide them here only as reference to make realistic projections. No-
tice that the traffic in the DL is higher than in the UL due to the fact the users download
258 The UMTS Network and Radio Access Technology
more information than they upload. We can also see that a good part of the subscriber
base remains in the open areas in this particular density distribution.
Consolidating 3G BS areas will vary from region to region. Some regions have already
strict regulations for the implementation of sites as well as high costs in dense areas.
This means that site acquisition will exceed the minimum requirements. Thus, Table 7.5
shows the necessary margins projected for subscriber growth assuming that sites can be
available within a short term. The turnaround to prepare sites to increase coverage and
capacity may not necessarily match a rapid subscriber growth. If we apply 50% of the
population coverage to the 1st case and 75% to the 2nd case, we then have about 750K
UMTS subscribers for the initial phase and about 1000K for the latter. This means we
dimension the 3G network initially with enough margin for growth towards the latter
phase where the subscriber base approaches the predicted numbers for 2005 in Table
7.1 when adding the 2G subscribers, i.e.
§.VXEVFULEHUV
7.6.3 Circuit Switched Data Calls Assumptions
From [1] for 64 kbps UDI we, assumed that 25% of the UMTS subscribers will also be
CS data subscribers. We also assume that 50% of the calls will be UL + DL, 25% of the
calls will be UL only and 25% of the calls will be DL only. This means, that one call
will occupy two channels (one for DL and one for UL) but with a 75% usage each.
CS data users may use multimedia with the following traffic mix:
use the link reference parameter, i.e. E
b
/N
o
, or energy per pit per noise power density,
which later will apply to the link budget frame work.
Picking it up from equation (2.6), we consider the generic reverse-link capacity in
CDMA
12
as the limiting factor. Thus, assuming perfect power control for this instance,
the received powers from all mobiles users are the same. Then
6
10
=
-
where M is the total number of active users in a given band, and where the total inter-
ference power in the band equals the sum of powers of single users. Now equating the
energy per bit to the average modulating signal power we defined
E
6
(67
5
==
where S is the average modulating signal power, T is bit time duration, and R is the bit
rate, i.e. 1/T. Then, incorporating the noise power density N
o
0
( 1(1
==
where G
p
corresponds to the system processing gain defined in equation (2.3), and M
defines the number of projected users in a single CDMA cell with omnidirectional an-
tenna without interference from neighbouring cells users transmitting continuously.
7.6.5.2 The Cell Loading Effect
Since in real 3G mobile networks there always exists more than one cell and more than
one sector, we need to introduce a loading effect due to interference from neighbouring
cells as follows:
_______
12
Mainly in rural areas; in urban area the downlink may/will become the limiting factor.
260 The UMTS Network and Radio Access Technology
()
E
R
(%
105
ËÛ
=
ÌÜ
-+b
,
$
,
$
p
p
qq
l=
ËÛ
q
qq
ÌÜ
ÌÜ
ÍÝ
×
×
where A
G
(0) is the peak antenna gain occurring generally at the bore sight (i.e.
A
G
is the horizontal antenna pattern of the sector antenna; I
represents the received
interference power from users of other cells as a function of
ËÛ
ËÛ
=l
ÌÜ
ÌÜ
-+bn
ÍÝ
ÍÝ
where may range from 40 to 50% for voice and 1% for data. Therefore, the value of
reduces the overall interference of the UL loading effect equation.
For the downlink (DL) we need an additional parameter
to reflect the orthogonality of
the transmission. Thus empirically, we can express it as:
()
E
R
(%
105
ËÛ
ËÛ
=l
ÌÜ
ÌÜ
--e+bn
ÍÝ
ÍÝ
microcell and picocell coverage.
Before describing the actual reference parameters for the link budgets in Table 7.7, in
the following we provide a generic background of the analysis steps for the forward and
reverse links.
7.6.6.1 The Forward Link
Applying the logic for the traffic channels analysis in Ref. [2], to the Dedicated Physical
Control Channel (DPCCH) and Dedicated Physical Data Channel (DPDCH) we can
formulate a generic E
b
/N
o
for the forward link in a multi-cellular environment.
Starting from a single cell with a single mobile station (MS),
E RR*
REQ
(3/$
*
1,,1
=
++
where P
o
is the BS sector traffic channel ERP in the direction of the MS within a given
antenna pattern with its angle
o
, L
o
equal to the path loss from the home BS in the di-
rection of
+++
When looking at a single cell with many MSs, the BS serves all MSs plus the MS under
consideration. Therefore, the latter gets the interference from the DL powers aimed at
the other MSs. We denote this additional interference as I
m
:
P*R
,
L
L
,$/3
=
=-e
Ê
ZKHUH DJDLQ
LV WKH RUWKRJRQDOLW\ IDFWRU DQG
P
i
is the forward traffic channel ERP
aimed for MS i, but radiated to the desired MS measuring E
b
/N
o
. P
i
may also denote the
is the total traffic channel ERP from BS k. Thus, I
t
represents the sum of all
traffic channel powers receive by the desired MS from all other BS, but excluding its
own. K is the total number of cells or sectors in the system under consideration. We can
define P
k
as
.
-
NM
M
3 3
=
=
Ê
The P
k
expression indicates that, for each BS k, we sum the forward traffic channel
ERPs for all MSs corresponding to that BS k.
The expression also implies that
M
3
is the traffic channel power aimed to MS j but cap-
tured by the MS calculating E
RQ5
(3/$
*
1,1
=
+
where P
R
is the reverse traffic channel ERP of the desired MS assuming an omnidirec-
tional transmit pattern, L
R
is the reverse path loss from the desired MS in the direction
of
o
to the home BS at given distance, A
GR
is the receive antenna gain of the home BS
in the direction of
o
to the desired MS, I
nR
is the power received at the home BS from
other interference from non-CDMA sources.
When considering a single cell with many mobiles one BS serves many MSs, and the
MS measuring E
b
/N
o
gets extra interference (I
the total reverse link interference generated by MS served by home BS. P
Rj
dynamically
changes based on the power control algorithm. Then, the reverse link E
b
/N
o
for a single
cell with many MS is:
E 55*5
RQ5P5
(3/$
*
1, , 1
=
++
In scenarios involving many MSs and multiple cells, the MS measuring E
b
/N
o
gets addi-
tional interference from MSs served by BSs from neighbouring cells. We can express
this interference as:
W5
N
.
5
N
We get P
Rk
by adding the powers of the traffic channels from MSs served by BS k,
where for this BS P
Rk,j
is the reverse traffic channel ERP of MS j; Likewise for BS k,
L
Rk,j
is the reverse path loss from MS j in the direction of
q
Rk,j
at a given distance. A
GR
is
the receiver antenna gain of the home BS in the direction of
q
Rk,j
to MS j served by BS
k. Then
264 The UMTS Network and Radio Access Technology
E 55*5
RQ5P5W5
(3/$
*
1, , ,1
=
++
The sum of the interfering elements divided by the thermal noise power N gives origin
(a
0
) Average Transmitter Power Per Traffic Channel (dBm)
Å
the mean of the total
transmitted power over an entire transmission cycle with maximum transmitted
power when transmitting.
(a
1
) Maximum Transmitter Power Per Traffic Channel (dBm)
Å
the total power at the
transmitter output for a single traffic
13
channel.
(a
2
) Maximum Total Transmitter Power (dBm)
Å
the aggregate maximum transmit
power of all channels.
(b) Cable, Connector, and Combiner Losses (Transmitter) (dB)
Å
the combined losses
of all transmission system components between the transmitter output and the an-
tenna input (all losses in + dB values).
(c) Transmitter Antenna Gain (dBi)
Å
the maximum gain of the transmitter antenna in
the horizontal plane (specified as dB relative to an isotropic radiator).
the noise figure of the receiving system referenced
to the receiver input.
(h), (H) Thermal Noise Density, No (dBm/Hz)
Å
the noise power per Hertz at the re-
ceiver input. Note that (h) is logarithmic units and (H) is linear units.
(i), (I) Receiver Interference Density (I
o
(dBm/Hz))
Å
the interference power per Hertz
at the receiver front end. This corresponds to the in-band interference power di-
vided by the system bandwidth. Note that (i) is logarithmic units and (I) is linear
units. Receiver interference density I
o
for a forward link is the interference power
per Hertz at the MS receiver located at the edge of coverage, in an interior cell.
(j) Total Effective Noise Plus Interference Density (dBm/Hz)
Å
the logarithmic sum of
the receiver noise density and the receiver noise figure and the arithmetic sum with
the receiver interference density.
(k) Information Rate (10log(R
b
)) (dBHz)
Å
the channel bit rate in (dBHz); the choice
of R
b
must be consistent with the E
Å
the effective gain achieved using diversity tech-
niques. If the diversity gain has been included in the E
b
/(N
o
+ I
o
) specification, it
should not be included here.
(o
) Other Gain (dB)
Å
additional gains, e.g. Space Diversity Multiple Access (SDMA)
may provide an excess antenna gain.
(p) Log-Normal Fade Margin (dB)
Å
defined at the cell boundary for isolated cells
corresponds to the margin required to provide a specified coverage availability over
the individual cells.
(q) Maximum Path Loss (dB)
Å
the maximum loss that permits minimum SRTT per-
formance at the cell boundary. Maximum path loss = d1 – m + (e–f) + o + o
+ n –
p.
(r) Maximum Range, R
max
2
–b+c) dBm dBm
(e) Receiver antenna gain (e.g. 18 dBi vehicular., 10
dBi pedestrian., 2 dBi indoor)
0 dBi Will vary
(f) Cable and connector losses 0 dB 2 dB
(g) Receiver noise figure 5 dB 5 dB
(h) Thermal noise density (H) (linear units) –174 dBm/Hz
3.98 10
–18
mW/Hz
–174 dBm/Hz
3.98 10
–18
mW/Hz
(i) Receiver interference density
(I) (linear units)
dBm/Hz
mW/Hz
dBm/Hz
mW/Hz
(j) Total effective noise plus interference density
= 10 log (10
((g+h) /10)
+ I)
dBm/Hz dBm/Hz
(k) Information rate (10 log (R
b
/N
o
values and the link budget in the
last two sections, we now look at the practical design factors having impact on coverage.
Coverage may not be an issue at the introduction of UMTS in some regions, because the
requirements will be gradual. However, from the service side, to back a pragmatic busi-
ness case, a network will most likely start with about 50% coverage of populated areas
as mentioned at the beginning of this chapter. Thus, such coverage will depend to a
good degree on service strategy. From the network design side, this implies that good
indoor coverage for high rate services will require dense sites in the urban areas with
Deploying 3G Networks 267
downlink limitation and less dense in rural areas with uplink limitation. The latter im-
plies that coverage and capacity trade-off will go hand in hand even at the beginning of
UMTS service. Here we are mainly concerned with coverage.
7.6.7.1 Uplink (UL) and Downlink (DL) Coverage
DL coverage depends primarily on the load because the transmission power may remain
the same despite the number of MSs active in a given BS, where all share the same
power. This means that DL coverage will decrease as a function of the number of MSs
and their transmission rates. The latter implies that additional power will afford better
coverage for higher rates in the DL.
In WCDMA higher transmission rates imply more spreading, which results in lower
processing gain, thereby smaller coverage. On the other hand, higher bit rates (demand-
ing more transmission power), require lower E
b
/N
o
because the extra power allows bet-
ter channel estimation, thereby compensating for larger
14
coverage. In relation to the
Ã
Ã
$
Ã
!
Ã
!!xi
Ã
##xi
Ã
"'#xi
Ã
!#xi
Ã
diversity gain, advanced BS signal processing techniques, and receiver antenna diver-
sity.
In the first case, when looking at characteristics of the reference multi-path channels in
Chapter 2, we see that the vehicular channels have more taps that those for the pedes-
trian ones. More taps implies higher multi-path diversity gain and thereby larger cover-
age.
In the second case, in the absence of high multi-path diversity gain during soft hand-
over, i.e. when the MS receives a signal from at least two BSs, the probability of accu-
rate signal detection increases resulting in higher micro-diversity gain.
Better baseband processing, e.g. adaptive filters for fading environments will improve
error rates and thereby lower E
b
/N
o
values, which in turn will increase coverage.
Finally, through antenna diversity techniques we can also get a coverage gain of 2–
3 dB. For example, transmit diversity can use two independent transmit paths from the
base station to the mobile, in order to mitigate the effect of fading. The two paths may
come from using two spatially separated antennas, or by using the two orthogonal po-
larizations of one cross-polarised antenna [5,6]. On the uplink, two-branch diversity
combining or Maximal Ratio Combining (MRC) is optimal when the traffic consists of
voice users only. However, when individual high data rate users are also present a fully
adaptive two branch Minimum Mean Squared Estimate (MMSE) algorithm will provide
improved performance by cancelling the interference due to these users. This cancella-
tion results in a gain in the order of 1.5 dB.
As mentioned earlier, in the DL we can add power gradually when necessary, thereby
increasing coverage for higher rates. However, this may not be the case in the UL be-
cause the MS has limited power. For example, a handset with an average power capac-
ity of 21 dBm will have a maximum of 26 or 27 dBm power; the latter if we assume the
MS gains 5–6 dBm at the BS due to the high reception sensitivity, antenna diversity and
cells should not exceed 75% in the DL and about 55% in the UL. On the other hand,
microcells can probably take 65% UL and 85% loading, respectively. This means we
need to apply the appropriate orthogonality factors when utilizing the load equations
described generically in Section 7.6.5.
The number of orthogonal codes also has impact on DL capacity despite a good propa-
gation environment and good load sharing. The maximum number of orthogonal codes
depends on the Spreading Factor (SF). For example, in general only one scrambling
code and thus only one code three gets used per sector in the BS, where common and
dedicated channels share the same three. On the other hand, the number of orthogonal
codes does not imply complete
16
limitation when enabling DL capacity, because we can
apply a 2nd scrambling code. However, the 1st and 2nd codes will not remain orthogo-
nal to one another, and channels with the 2nd code interfere more with the channels
with the 1st code.
7.7 D
IMENSIONING
RNC I
NTERFACES
When dimensioning the RNC Iub interface, i.e. the connection between the Node B and
RNC, we also consider the traffic mix in order to determine the number of RNCs re-
quired. Thus, RNC interface dimensioning will take into account the number of Node
Bs and the projected type of services with the forecasted subscribers and their traffic
profiles [7].
Figure 7.9 illustrates the UTRAN interface configuration.
7.7.1 Dimensioning the Iub
The average traffic per Node B provide the total traffic based on the service mix statis-
tics, the soft handover traffic and overheads, signaling and O&M traffic.
IqrÃ7
a
i
, plus signalling overheads and
O&M margins. Here we assume that the ratio peak traffic over average traffic corre-
sponds to the burstiness factor
b
.
We then calculate the overall PDF(R
a
) and CDF(R
a
), where R
a
corresponds to the ag-
gregate bit rate to determine the outage probability for each value of the user bit rate.
Afterwards we obtain a set of outage probabilities, which corresponds one to each user
bit rate R
b
. At the end we dimension the channel capacity by fixing a common outage
probably value P
0
for each service i.
7.7.1.1 Iub Total Traffic
As indicated in the preceding section, after we calculate the peak traffic per Node B, we
take into account additional overheads and signaling loads. Thus, we obtain the total
traffic at the Iub interface from the user information traffic, soft handover traffic,
burstiness factor and overheads as well as signaling margins. Typical assumptions for
the margins include: O&M = 10%, signaling = 20%, and ATM overhead = 40% of the
Iub peak user traffic, respectively. In summary, we can define the Total Iub traffic as:
7RWDO,XEWUDIILF SHDNWUDIILF20VLJQDOLQJRYHUKHDG
The Iub, Iu, and Iur interfaces will in general support sufficient capacity margins, and
the overheads will not exceed peak rates. Thus, the key RNC dimensioning parameters
include the number of Node Bs in the coverage area, and the average traffic in this
given area. The first parameter gives the:
51&
Ifqrf7
7RWDOQRQRGH%VQR1RGH%VVXSSRUWHGSHU51&
and the second one allows us to calculate throughput capacity, i.e. RNC
throughput
=
max
ÒÎ
CS
avg
/X
1
Þ
,
Î
PS
avg
/Y
1
Þâ
. We can obtain the initial value of RNC
throughput
from the
CS and PS average traffic uniformly distributed in the target area.
We can modify the PS (Mbps) vs. CS (Erlang) output of Figure 7.10 to a PS vs. CS
(Mbps) output by translating the CS traffic from Erlang to Mbps (i.e. Erlang × 12.2
Figure 7.11 Estimation of the RNC throughput.
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